A new double EWMA-t chart for process mean

Abstract

The EWMA-t chart is used to monitor the process mean as it is robust against errors in estimating the process standard deviation or changing standard deviation. In this paper, we propose a double EWMA-t (DEWMA-t) chart for monitoring the process mean, which is a natural extension of the EWMA-t chart. The idea is to first construct the t chart using the EWMA statistic, and then put it into another EWMA statistic to devise the DEWMA-t chart. The DEWMA-t chart encompasses the EWMA-t chart. The Monte Carlo simulation method is used to compute the run length properties of the DEWMA-t chart. Based on detailed run length comparisons, it turns out that, with some reasonable assumptions, the DEWMA-t chart performs uniformly and substantially better than the EWMA-t chart when detecting different kinds of shift in the process mean. A similar trend is observed when these control charts are compared with their counterparts based on the variable sampling interval feature. In addition, real datasets are also used to support the theory.

Keywords:

• Average run length
• Control chart
• EWMA
• DEWMA
• Monte Carlo simulation
• Process mean
• Statistical process control

Acknowledgments

The authors are thankful to the associate editor and the anonymous reviewer(s) for providing useful comments that led to an improved version of the article.